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The Importance of Data Governance

Answering key questions to help you understand the importance of data governance and build a plan that works for your business.

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Data governance is essential for any organization that collects, stores, and uses data, which, in today’s digital landscape, applies to pretty much every business. But what exactly is data governance and why is it so important? Get the answers to these questions and learn how to build a data governance plan that meets your business needs.

What is Data Governance?

Data governance refers to the overall management and control of an organization’s data assets, including the processes, policies, and rules that ensure data quality, security, and compliance. Implementing a data governance strategy requires the creation of guidelines for data usage, defined roles and responsibilities throughout the organization, and effective strategies for handling data at different stages of its lifecycle.

The difference between data governance and other data strategies like data management in that data governance focuses on the strategic management and control of data assets while data management focuses on the operational aspects of handling and manipulating data. Where data management looks at things like data storage, integration, cleansing, and analysis, data governance sets a framework of rules and procedures for how data should be handled in each scenario.

Why is Data Governance Important?

There are a number of reasons why data governance is important, including ensuring the reliability of data, protecting data security, improving traceability and transparency, conforming to compliance regulations, and providing the necessary framework to maintain data consistency. All of the positive outcomes of a well-developed data governance plan come together to enhance decision making within an organization and to establish trust both within the data itself and the company as a whole.

Data Reliability

Reliable data is the foundation of any data driven decision. You can’t make good decisions off bad data, so ensuring that the data your organization is using to make decisions is reliable is one of the most important aspects of a data governance program. Data reliability is safeguarded by establishing processes and practices for accurate and consistent data collection, storage, and usage.


Data governance also plays a vital role in data security by defining access controls, data protection measures, and privacy policies to safeguard sensitive information from unauthorized access. By prioritizing data governance, organizations can effectively mitigate the risks associated with data breaches, protect customer information, and maintain a solid foundation of trust and credibility.


Furthermore, data governance enables and improves traceability, allowing organizations to track the original lineage of data, ensuring accountability and auditability. Being able to track the journey of data from its origin to its final destination enables the organization to address data quality issues, inconsistencies, and discrepancies at the source.


Compliance with regulatory requirements is also facilitated through data governance, as it ensures adherence to legal obligations and industry standards. Regulations such as the Health Insurance Portability and Accountability Act (HIPAA), and the General Data Protection Regulation (GDPR) in the U.S. and the Personal Information Protection and Electronic Documents Act (PIPEDA), Personal Health Information Protection Act (PHIPA), and the Digital Privacy Act in Canada, all require data governance measures to be in place in order to meet regulatory standards.

How to Develop a Data Governance Strategy

Now that you understand the importance of data governance, it’s time to start building your data governance strategy. Developing a data governance strategy requires a systematic and comprehensive approach that aligns with your organization’s goals, culture, and data landscape. While the specifics will look different depending on your company’s needs, there are some general best practices that you can follow to help structure and implement your unique data governance strategy.

1. Define the Core Objectives

The first step in developing an effective data governance strategy is to clearly define the objectives and goals of the strategy. Identify what your organization aims to achieve, whether that be improving data quality, ensuring regulatory compliance, or enhancing data security. Setting clear objectives at the start will help guide the strategy development process and avoid confusion during implementation.

2. Assess Your Data Landscape

A key step in the early stages of developing your data governance strategy is to assess your current data landscape. Identify the types of data collected, how it’s stored and processed, as well as your data sources, systems, and stakeholders. Understanding existing data management practices, data quality issues, and potential risks will help you to determine which areas will need the most governance.

3. Establish a Governance Structure

In order to create a solid data governance structure, the specific roles, responsibilities, and decision-making processes involving data management need to be outlined in detail. This includes appointing a data governance team or committee comprised of representatives from across the organization to oversee and enforce data governance initiatives.

4. Develop Policies and Standards

Now that you’ve done the leg work to define your objectives, assess your current data landscape, and establish a governance structure, it’s time to start developing the specific policies and standards that will make up the heart of your strategy. Your policies, standards, and guidelines should align with your organizational objectives as well as and regulatory requirements that your industry is subject to.

Your governance policies should be clear, concise, and cover all relevant aspects of data governance including:

· data classification

· data ownership

· data access controls

· data retention

· data quality standards

· data privacy

· security protocols

5. Define Data Governance Processes

Once your policies and standards are in place, it’s time to develop the processes and workflows for specific data governance activities.

Such activities include:

· data classification

· data tagging

· data documentation

· metadata management

· data integration

· data access requests

· data quality monitoring, data lifecycle management

· data stewardship

Documenting these processes ensures consistency in the handling of data and clarity during implementation and training.

6. Implement Data Security Measures

A significant part of your data governance strategy should be used to address data security measures.

To ensure effective data protection measures are in place be sure to address all of the following:

· access controls

· encryption protocols

· data masking

· data anonymization

· scheduled security audits

7. Foster Awareness and Build a Data-Driven Culture

Creating a data-driven culture is its own worthwhile undertaking, but it is especially important when working to establish and enforce a company-wide data governance strategy. Emphasize the importance of data governance and data management practices by providing training and awareness programs to educate employees about their roles and responsibilities in maintaining data quality, privacy, and security.

Encouraging data literacy and promoting a sense of accountability towards data governance initiatives will help improve employee buy-in and make the implementation process easier. For more on this topic, check out our blog post 7 Steps to Creating a Data-Driven Work Culture.

8. Monitor, Evaluate, Adapt, and Evolve

Data governance is not a one-time project that can be implemented and then forgotten, it requires constant revision in order to adjust to new types of data, new strategies, and changing business landscapes. First, establish mechanisms to continuously monitor and evaluate the effectiveness of your data governance strategy. Regularly assess data quality, compliance levels, policy adherence, and overall performance to identify areas for improvement. The policies, standards, and practices laid out in your data governance strategy should be reviewed and updated to reflect changes in the organization’s data landscape, business needs, and regulatory requirements.

Get Help from the Experts at Kwixand Solutions

Are you ready to get started developing and implementing a data governance strategy to fit your business but still not sure where to start? Kwixand Solutions has the tools and knowledge you need to help build, implement, and support your custom data governance strategy. Schedule a free consultation with one of our experienced Kwixand Solutions business consultants today.

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